An integrated device, the device including: a first level including a first mono-crystal layer, the first mono-crystal layer including a plurality of single crystal transistors; an overlaying oxide on top of the first level; a second level including a second mono-crystal layer, the second level overlaying the oxide, where the second mono-crystal layer includes a plurality of first image sensors; and a third level overlaying the second level, where the third level includes a plurality of second image sensors, where the second level is bonded to the first level, where the bonded includes an oxide to oxide bond; and an isolation layer disposed between the second mono-crystal layer and the third level.
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8. An integrated device, the device comprising:
a first level comprising a first mono-crystal layer, said first level comprising a plurality of single crystal transistors;
an overlaying oxide on top of said first level;
a second level comprising a second mono-crystal layer, said second level overlaying said oxide,
wherein said second mono-crystal layer comprises a plurality of first image sensors; and
a third level overlaying said second level,
wherein said third level comprises a plurality of second image sensors, and
wherein said second level is bonded to said first level; and
memory circuits.
9. An integrated device, the device comprising:
a first level comprising a first mono-crystal layer,
wherein said first mono-crystal layer comprises a plurality of single crystal transistors;
an overlying oxide on top of said first level;
a second level comprising a second mono-crystal layer, said second level overlaying said oxide;
a third level overlaying said second level,
wherein said third level comprises a third mono-crystal layer comprising a plurality of image sensors,
wherein said second level is bonded to said first level, and
wherein said bonded comprises oxide to oxide bonds; and
an isolation layer disposed between said second mono-crystal layer and said third level.
1. An integrated device, the device comprising:
a first level comprising a first mono-crystal layer, said first mono-crystal layer comprising a plurality of single crystal transistors;
an overlaying oxide on top of said first level;
a second level comprising a second mono-crystal layer, said second level overlaying said oxide,
wherein said second mono-crystal layer comprises a plurality of first image sensors; and
a third level overlaying said second level,
wherein said third level comprises a plurality of second image sensors,
wherein said second level is bonded to said first level,
wherein said bonded comprises an oxide to oxide bond; and
an isolation layer disposed between said second mono-crystal layer and said third level.
2. The integrated device according to
wherein said second mono-crystal layer is less than 5 microns thick.
3. The integrated device according to
wherein said first level comprises a plurality of landing pads.
4. The integrated device according to
wherein said second mono-crystal layer comprises alignment marks, and
wherein said third level is aligned to said alignment marks.
6. The integrated device according to
wherein said plurality of first image sensors is sensitive to a first set of light wavelengths and said plurality of second image sensors is sensitive to a second set of light wavelengths, and
wherein said first set of light wavelengths is different than said second set of light wavelengths.
7. The integrated device according to
wherein said second level comprises an array of image sensor pixels,
wherein said first level comprises a plurality of pixel control circuits, and
wherein each of said image sensors pixels is directly connected to said pixel control circuits.
10. The integrated device according to
wherein said second mono-crystal layer is less than 5 microns thick.
11. The integrated device according to
wherein said first level comprises a plurality of landing pads.
13. The integrated device according to
wherein said second mono-crystal layer comprises a plurality of second image sensors.
14. The integrated device according to
wherein said third level comprises an array of image sensor pixels, and
wherein said first level comprises a plurality of pixel control circuits.
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This application is a continuation-in-part of U.S. patent application Ser. No. 17/317,894 filed on May 12, 2021, which is a continuation-in-part of U.S. patent application Ser. No. 17/143,956 filed on Jan. 7, 2021, now U.S. Pat. No. 11,043,523 issued on Jun. 22, 2021; which is a continuation-in-part of U.S. patent application Ser. No. 17/121,726 filed on Dec. 14, 2020, now U.S. Pat. No. 10,978,501 issued on Apr. 13, 2021; which is a continuation-in-part of U.S. patent application Ser. No. 17/027,217 filed on Sep. 21, 2020, now U.S. Pat. No. 10,943,934 issued on Mar. 9, 2021; which is a continuation-in-part of U.S. patent application Ser. No. 16/860,027 filed on Apr. 27, 2020, now U.S. Pat. No. 10,833,108 issued on Nov. 11, 2020; which is a continuation-in-part of U.S. patent application Ser. No. 15/920,499 filed on Mar. 14, 2018, now U.S. Pat. No. 10,679,977 issued on Jun. 9, 2020; which is a continuation-in-part of U.S. patent application Ser. No. 14/936,657 filed on Nov. 9, 2015, now U.S. Pat. No. 9,941,319 issued on Apr. 10, 2018; which is a continuation-in-part of U.S. patent application Ser. No. 13/274,161 filed on Oct. 14, 2011, now U.S. Pat. No. 9,197,804 issued on Nov. 24, 2015 and this application is a continuation-in-part of U.S. patent application Ser. No. 12/904,103 filed on Oct. 13, 2010, now U.S. Pat. No. 8,163,581 issued on Apr. 24, 2012; the entire contents of all of the preceding are incorporated herein by reference.
This invention describes applications of monolithic 3D integration to various disciplines, including but not limited to, for example, light-emitting diodes, displays, image-sensors and solar cells.
Semiconductor and optoelectronic devices often require thin monocrystalline (or single-crystal) films deposited on a certain wafer. To enable this deposition, many techniques, generally referred to as layer transfer technologies, have been developed. These include:
Background on Image-Sensors:
Image sensors are used in applications such as cameras. Red, blue, and green components of the incident light are sensed and stored in digital format. CMOS image sensors typically contain a photodetector and sensing circuitry. Almost all image sensors today have both the photodetector and sensing circuitry on the same chip. Since the area consumed by the sensing circuits is high, the photodetector cannot see the entire incident light, and image capture is not as efficient.
To tackle this problem, several researchers have proposed building the photodetectors and the sensing circuitry on separate chips and stacking them on top of each other. A publication that describes this method is “Megapixel CMOS image sensor fabricated in three-dimensional integrated circuit technology”, Intl. Solid State Circuits Conference 2005 by Suntharalingam, V., Berger, R., et al. (“Suntharalingam”). These proposals use through-silicon via (TSV) technology where alignment is done in conjunction with bonding. However, pixel size is reaching the 1 μm range, and successfully processing TSVs in the 1 μm range or below is very difficult. This is due to alignment issues while bonding. For example, the International Technology Roadmap for Semiconductors (ITRS) suggests that the 2-4 um TSV pitch will be the industry standard until 2012. A 2-4 μm pitch TSV will be too big for a sub-1 μm pixel. Therefore, novel techniques of stacking photodetectors and sensing circuitry are required.
A possible solution to this problem is given in “Setting up 3D Sequential Integration for Back-Illuminated CMOS Image Sensors with Highly Miniaturized Pixels with Low Temperature Fully-depleted SOI Transistors,” IEDM, p. 1-4 (2008) by P. Coudrain et al. (“Coudrain”). In the publication, transistors are monolithically integrated on top of photodetectors. Unfortunately, transistor process temperatures reach 600° C. or more. This is not ideal for transistors (that require a higher thermal budget) and photodetectors (that may prefer a lower thermal budget).
Background on CCD Sensors:
Image sensors based on Charge-Coupled Device (CCD) technology has been around for several decades. The CCD technology relies on a collect and shift scheme, wherein charges are collected in individual cells according to the luminosity of the light falling on each of them, then the charges are sequentially shifted towards one edge of the sensor where readout circuits read the sequence of charges one at a time.
The advantage of CCD technology is it has better light sensitivity since almost the entire CCD cell area is dedicated to light collecting, and the control and readout circuits are all on one edge not blocking the light. On the other hand, in a CMOS sensor, the photodiodes in each cell have to share space with the control and readout circuits adjacent to them, and so their size and light sensitivity are therefore limited.
The main issue with CCD technology is this sequential shifting of image information from cell to cell is slow and limits the speed and cell density of CCD image sensors. A potential solution is to put the readout circuits directly under each CCD cell, so that the information is read in parallel rather than in time sequence, thus removing the shifting delay entirely.
Background on High Dynamic Range (HDR) Sensors:
Ever since the advent of commercial digital photography in the 1990s, achieving High Dynamic Range (HDR) imaging has been a goal for most camera manufacturers in their image sensors. The idea is to use various techniques to compensate for the lower dynamic range of image sensors relative to the human eye. The concept of HDR however, is not new. Combining multiple exposures of a single image to achieve a wide range of luminosity was actually pioneered in the 1850s by Gustave Le Gray to render seascapes showing both the bright sky and the dark sea. This was necessary to produce realistic photographic images as the film used at that time had extremely low dynamic range compared to the human eye.
In digital cameras, the typical approach is to capture images using exposure bracketing, and then combining them into a single HDR image. The issue with this is that multiple exposures are performed over some period of time, and if there is movement of the camera or target during the time of the exposures, the final HDR image will reflect this by loss of sharpness. Moreover, multiple images may lead to large data in storage devices. Other methods use software algorithms to extract HDR information from a single exposure, but as they can only process information that is recordable by the sensor, there is a permanent loss of some details.
In another aspect, a method using layer transfer for fabricating a CCD sensor with readout circuits underneath so as to collect image data from each cell in parallel, thus eliminating the shifting delay inherent in the traditional CCD charge transfer sequencing scheme.
In another aspect, a method using layer transfer for fabricating an image sensor consisting of one layer of photo-detectors with small light-sensitive areas, stacked on top of another layer of photo-detectors with larger light-sensitive areas.
In another aspect, a method using layer transfer for fabricating two image sensor arrays monolithically stacked on top of each other with an insulating layer between them and underlying control, readout, and memory circuits.
In another aspect, algorithms for reconstructing objects from images detected by a camera which includes a lens and two image sensor arrays of distinct distances from the lens.
In another aspect, a gesture remote control system using images detected by a camera which includes a lens and two image sensor arrays of distinct distances from the lens.
In another aspect, a surveillance camera system using images detected by a camera which includes a lens and two image sensor arrays of distinct distances from the lens.
In another aspect, a method of constructing a camera which includes a lens and two image sensor arrays of distinct effective distances from the lens, wherein images from the lens are split between the two image sensors by a beam-splitter.
In another aspect, a method of constructing a camera which includes a lens, an image sensor array, and a fast motor, wherein the fast motor actuates the image sensor's position relative to the lens so as to record images from the lens at distinct effective distances from the lens.
In another aspect, a camera system including, a first image sensor array and a second image sensor array wherein the first image sensor array is designed for a first focal plane in front of the camera, and the second image sensor array is designed for a second focal plane in front of the camera, wherein the distance to the first focal plane is substantially different than the distance to the second focal plane.
In another aspect, a camera system including, an image sensor sub system and a memory subsystem and a control subsystem wherein the camera is designed wherein the image sensor can provide the memory of at least a first image and a second image for the same scene in front of the camera, wherein the first image is for a first focal plane in front of the camera, and the second image is for a second focal plane in front of the camera, wherein the distance to the first focal plane is substantially different than the distance to the second focal plane.
In another aspect, a camera system including, a first image sensor array and a second image sensor array wherein the first image sensor array includes a first mono-crystallized silicon layer, and the second image sensor array includes a second mono-crystallized silicon layer, wherein between the first mono-crystallized silicon layer and second mono-crystallized silicon layer there is a thin isolation layer, wherein through the thin isolation layer there are a multiplicity conducting vias wherein the conducting vias radius is less than 400 nm.
In another aspect, a camera system including, a first image sensor array and a second image sensor array wherein the first image sensor array includes a first mono-crystallized silicon layer, and the second image sensor array includes a second mono-crystallized silicon layer, wherein between the first mono-crystallized silicon layer and second mono-crystallized silicon layer there is a thin isolation layer, wherein the second mono-crystallized silicon layer thickness is less than 400 nm.
In another aspect, an integrated device, the device comprising: a first level comprising a first mono-crystal layer, said first mono-crystal layer comprising a plurality of single crystal transistors and alignment marks; an overlaying oxide on top of said first level; a second level comprising a second mono-crystal layer, said second level overlaying said oxide, wherein said second mono-crystal layer comprises a plurality of first image sensors; and a third level overlaying said second level, wherein said third level comprises a plurality of second image sensors, wherein said second level is aligned to said alignment marks, wherein said second level is bonded to said first level, and wherein said bonded comprises an oxide to oxide bond.
In another aspect, an integrated device, the device comprising: a first level comprising a first mono-crystal layer, said first mono-crystal layer comprising a plurality of single crystal transistors and alignment marks; an overlaying oxide on top of said first level; a second level comprising a second mono-crystal layer, said second level overlaying said oxide, wherein said second mono-crystal layer comprises a plurality of first image sensors; and a third level overlaying said second level, wherein said third level comprises a plurality of second image sensors, and wherein said second level is bonded to said first level.
In another aspect, an integrated device, the device comprising: a first level comprising a first mono-crystal layer, said first mono-crystal layer comprising a plurality of single crystal transistors and alignment marks; an overlaying oxide on top of said first level; a second level comprising a second mono-crystal layer, said second level overlaying said oxide, wherein said second mono-crystal layer comprises a plurality of first image sensors; and a third level overlaying said second level, wherein said third level comprises a plurality of second image sensors, and wherein said second level is bonded to said first level.
In another aspect, an integrated device, the device comprising: a first level comprising a first mono-crystal layer, said first mono-crystal layer comprising a plurality of single crystal transistors; an overlaying oxide on top of said first level; a second level comprising a second mono-crystal layer, said second level overlaying said oxide, wherein said second mono-crystal layer comprises a plurality of first image sensors; and a third level overlaying said second level, wherein said third level comprises a plurality of second image sensors, wherein said second level is bonded to said first level, wherein said bonded comprises an oxide to oxide bond; and an isolation layer disposed between said second mono-crystal layer and said third level.
In another aspect, an integrated device, the device comprising: a first level comprising a first mono-crystal layer, said first level comprising a plurality of single crystal transistors; an overlaying oxide on top of said first level; a second level comprising a second mono-crystal layer, said second level overlaying said oxide, wherein said second mono-crystal layer comprises a plurality of first image sensors; and a third level overlaying said second level, wherein said third level comprises a plurality of second image sensors, and wherein said second level is bonded to said first level.
In another aspect, an integrated device, the device comprising: a first level comprising a first mono-crystal layer, wherein said first mono-crystal layer comprises a plurality of single crystal transistors; an overlying oxide on top of said first level; a second level comprising a second mono-crystal layer, said second level overlaying said oxide; a third level overlaying said second level, wherein said third level comprises a third mono-crystal layer comprising a plurality of image sensors, wherein said second level is bonded to said first level, and wherein said bonded comprises oxide to oxide bonds; and an isolation layer disposed between said second mono-crystal layer and said third level.
Various embodiments of the invention will be understood and appreciated more fully from the following detailed description, taken in conjunction with the drawings in which:
Embodiments of the present invention are now described with reference to
NuImager Technology:
Layer transfer technology can also be advantageously utilized for constructing image sensors. Image sensors typically include photodetectors on each pixel to convert light energy to electrical signals. These electrical signals are sensed, amplified and stored as digital signals using transistor circuits.
Step (A) is illustrated in
Step (B) is illustrated in
Step (C) is illustrated in
Step (D) is illustrated in
Step (E) is illustrated in
Step (F) is illustrated in
Various elements in
Step (G) is illustrated using
Step (H) is illustrated in
As mentioned previously,
While Silicon has been suggested as the material for the photodetector layer of
While
One of the common issues with taking photographs with image sensors is that in scenes with both bright and dark areas, while the exposure duration or shutter time could be set high enough to get enough photons in the dark areas to reduce noise, picture quality in bright areas degrades due to saturation of the photodetectors' characteristics. This issue is with the dynamic range of the image sensor, i.e. there is a tradeoff between picture quality in dark and bright areas.
Confocal 3D Microscopy with Screen Made of Stacked Arrays of Modulators:
Confocal Microscopy is a method by which 3D image information from a specimen is preserved. Typically, confocal microscopy is used in conjunction with the technique of inducing florescence from the specimen by shining laser light upon it. The laser light is absorbed by the specimen which then re-emits the light at a lower energy level (longer wavelength). This secondary light or florescence is then imaged by the confocal microscopy system.
By moving the screen and its aperture up, down, left, right, forward, and backward, light from specific points of the specimen are detected and so a 3D image of the specimen can then be reconstructed. Conversely, one may also move the specimen in the same manner instead of the screen to achieve the same objective of scanning the specimen.
The issue with such a scanning scheme is that mechanical scanning is slow and requires more space to allow for the movements. An alternative is to replace the screen with a 3D array of optical modulators that control the passage of light, thus allowing much faster scanning through electronic control.
In such manner, a 3D image can be scanned and reconstructed from the images detected by the electronic scanning of the aperture.
Layer transfer technology may be utilized for constructing the layers for a 3D optical modulator array system. A 3D optical modulator system may contain control circuits, and a stack of optical modulators.
The process of forming the 3D optical modulator array may include several steps that occur in a sequence from Step A to Step E. Many of these steps share common characteristics, features, modes of operation, etc. When identical reference numbers are used in different drawing figures, they are used to indicate analogous, similar or identical structures to enhance the understanding of the present invention by clarifying the relationships between the structures and embodiments presented in the various diagrams—particularly in relating analogous, similar or identical functionality to different physical structures.
Step (A):
Step (B):
Step (C):
Step (D) is illustrated in
As described previously,
Hydrogen may be implanted in the wafer at a certain depth depicted by dashed line 3689.
Steps (B)-(D) may be repeated as often as needed to stack as many optical modulator layers as necessary.
Step (E) is illustrated in
Various elements of
Persons of ordinary skill in the art will appreciate that while Silicon and Germanium have been suggested as the material for the optical modulator layers of
CCD Sensor With Parallel Readout Circuits
The main issue with CCD technology is the sequential shifting of image information from cell to cell is slow and limits the speed and cell density of CCD image sensors. A potential solution is to put the readout circuits directly under each CCD cell, so that the information is read in parallel rather than in time sequence, thus removing the shifting delay entirely.
Instead of shifting charges one-by-one, the data can be read in parallel by a readout circuit constructed underneath the CCD sensor. Layer transfer technology may be utilized for constructing the layers for a stacked CCD with underlying readout circuits.
The process of forming the CCD-control circuit stack may include several steps that occur in a sequence from Step A to Step D. Many of these steps share common characteristics, features, modes of operation, etc. When identical reference numbers are used in different drawing figures, they are used to indicate analogous, similar or identical structures to enhance the understanding of the present invention by clarifying the relationships between the structures and embodiments presented in the various diagrams—particularly in relating analogous, similar or identical functionality to different physical structures.
Step (A):
Step (B):
A connections is made to the p-type Si substrate 3762 by lithographic, etch, and fill operations similar to those described in
Step (C) is illustrated in
As described previously,
Various elements of
Step (D) is illustrated in
Persons of ordinary skill in the art will appreciate that while Silicon has been suggested as the material for the CCD substrate layers of
Stacked High Dynamic Range (HDR) Sensor:
In digital cameras, the typical approach is to capture images using exposure bracketing, and then combining them into a single HDR image. The issue with this is that multiple exposures are performed over some period of time, and if there is movement of the camera or target during the time of the exposures, the final HDR image will reflect this by loss of sharpness. Moreover, multiple images may lead to large data in storage devices. Other methods may use software algorithms to extract HDR information from a single exposure, but as they can only process information that is recordable by the sensor, there is a permanent loss of some details.
A solution may be to use image sensors that have HDR capability. A single layer of photo-detectors within the image sensor is hard-pressed to achieve this. In the case where the light-collecting area is small, the photo-detector is capable of detecting minute amounts of photocurrent but may saturate quicker, whereas when the light-collecting area is large, the photo-detector is capable of handling large amounts of light, but may not be able to detect small photocurrents. Combining them by stacking allows a photo-detector cell to have the capability to detect both low and high luminosity without saturating.
Step (A):
Step (B):
Step (C):
Persons of ordinary skill in the art will appreciate that while Silicon has been suggested as the material for the HDR photo-detector layers of
2-Sensor Camera System:
Step (A):
Step (B):
Persons of ordinary skill in the art will appreciate that while Silicon has been suggested as the material for the photo-detector layers of
For reconstructing images on planes on either side of the lens 4112, image mapping may be performed using algorithms from Fourier optics utilizing the Fourier transform, available through commercial packages such as the MATLAB Image Processing Toolbox. It will be useful to recall here the Lens-maker's equation which states that for an object on a plane at a distance o from a lens of focal length f where f<<o, the focal image plane of the object will lie at a distance i on the opposite side of the lens according to the equation: 1/o+1/i=1/f.
For the image reconstruction algorithms discussed herein, the following notations will be used:
d:=distance from lens on real side
d0:=initial distance from lens on real side
z:=distance from lens on image side
s:=space step interval
f(s):=nonlinear step interval e.g. f(s)=s{circumflex over ( )}n
t:=time
t0:=starting time
ts:=time step interval
S1(i,j):=matrix data of image detected on front image sensor 4113
S2(i,j):=matrix data of image detected on back image sensor 4114
O(i,j):=reconstructed image from S1 and S2
OS(i,j):=stored reconstructed data O(i,j)
S1(i,j,t):=stored matrix data of image detected on front image sensor 4113 at time t
S2(i,j,t):=stored matrix data of image detected on back image sensor 4114 at time t
FIM(O, d, z):=forward image mapping (FIM) operation from an image O on the real side of the lens 4312 at distance d from lens 4312 to the image side of the lens 4312 at a distance z from lens 4312
BIM(O, d, z):=backward image mapping (BIM) operation from an image O on the image side of the lens 4312 at distance z from lens 4312 to the real side of the lens 4312 at a distance d from lens 4312
I1(i,j,d,z1):=FIM operation of object matrix upon S1(i,j) at specified d, and z=z1
I2(i,j,d,z2):=FIM operation of object matrix upon S2(i,j) at specified d, and z=z2
IS1(i,j):=stored I1 data
IS2(i,j):=stored I2 data
O1(i,j,d,z1):=BIM operation on S1(i,j) at specified d, z=z1
O2(i,j,d,z2):=BIM operation on S2(i,j) at specified d, and z=z2
Odiff(i,j):=O1(i,j,d,z)−O2(i,j,d,z) for every i, j
Odiff(i,j,k):=O1(i,j,d,z)−O2(i,j,d,z) for every i, j with k as the iteration variable if values are to be stored
ABS[a]:=absolute value operation on a scalar a
NORM[A]:=A matrix norm operation (for example, a 2-norm)
GET_SHARP[A]:=extract object within image data that exhibits the most contrast compared to its surroundings.
T:=error tolerance between the corresponding elements of 2 matrices
E:=error tolerance of any scalar comparison
FFT(M):=fast fourier transform operation on a matrix M
IFFT(M):=inverse fast fourier transform operation on a matrix M
OF(i,j):=O(i,j) in Fourier space
OF1(i,j):=O1(i,j) in Fourier space
OF2(i,j):=O2(i,j) in Fourier space
OFdiff(i,j):=OF1(i,j,d,z)−OF2(i,j,d,z) for every i, j
Step A (4140): choose d>>f, d1<=d<=d2
Step B (4142): calculate z from d using the lens-maker's formula
Step C (4144): O1 and O2 are calculated by BIM operations on S1 and S2 respectively
Step D (4146): Calculate Odiff:=O1−O2 for every element in the matrices O1 and O2
Step E (4148): Calculate the linear distance weighted estimate of the reconstructed object O(i,j) as expressed by:
For every i,j:
Step A (4160): choose d>>f, d1<=d<=d2
Step B (4162): calculate z from d using the lens-maker's formula
Step C (4164): O1 and O2 are calculated by BIM operations on S1 and S2 respectively
Step D (4166): OF1 and OF2 are calculated by FFT operations on O1 and O2 respectively
Step E (4168): OFdiff:=OF1−OF2 is calculated for every element in the matrices OF1 and OF2
Step F (4170): Calculate the linear distance weighted estimate of the reconstructed object OF(i,j) in Fourier space as expressed by:
For every i,j:
Step A (4180): Start with d=d0, d1<=d0<=d2, initialize IS1, IS2 as zero matrices
Step B (4181): Use Algorithm 41A or Algorithm 41B to calculate O(i,j)
Step C (4182): Check if d=d0, if yes go to Step D otherwise continue to Step E
Step D (4183): Store O(i,j) into OS(i,j)
Step E (4184): Calculate I1 and I2 by FIM operations on O(i,j)
Step F (4185): Take I1 and I2 out from sensor data S1 and S2 respectively.
Step G (4186): Add stored data IS1 and IS2 (I1 and I2 from previous step) to sensor data S1 and S2 respectively.
Step H (4187): Store current I1 and I2 into IS1 and IS2 respectively.
Step I (4188): Increment d by some interval function such as a geometric relationship.
Step J (4189): If d has not exceeded d2, loop back to Step B (4181) and continue from there
Step K (4190): If d has exceeded d2, reset d=d0
Step L (4191): Use Algorithm 41A or Algorithm 41B to calculate O(i,j)
Step M (4192): Compare O(i,j) with OS(i,j) using a matrix norm operation, and if within error tolerance, algorithm ends. Else algorithm loops back to Step C (4182) and continues on.
Step A (4240): starting d=d0 is chosen, d1<=d0<=d2
Step B (4242): calculate z from d using the lens-maker's formula
Step C (4244): O1 and O2 are calculated by BIM operations on S1 and S2 respectively
Step D (4246): Odiff:=O1−O2 is calculated for every element in the matrices O1 and O2
Step E (4248): NORM operation is performed on Odiff
Step F (4250): If the result of the NORM operation reveals a minimum,
then
Step G (4252): d* is found and z* is calculated,
else
Step H (4254): d is incremented by s and the steps B-F are repeated.
Step I (4256): Calculate the linear distance weighted estimate of the reconstructed object O(i,j) as expressed by:
For every i,j:
Step A (4260): starting d=d0 is chosen, d1<=d0<=d2
Step B (4262): calculate z from d using the lens-maker's formula
Step C (4264): O1 is calculated by BIM operation on S1
Step D (4266): Sharpness value of O1 is calculated and stored in OS
Step E (4268): If a sharpness maximum is found,
then
Step F (4270): d* is determined and z* is calculated
else
Step G (4272): d is incremented by s and steps B-E are repeated.
Step H (4274): O2 is calculated using BIM operation on S2 with d* and z*
Step I (4276): Odiff:=O1−O2 is calculated for every element in the matrices O1 and O2
Step J (4278): Calculate the linear distance weighted estimate of the reconstructed object O(i,j) as expressed by:
For every i,j:
Step A (4340): starting d=d0 is chosen
Step B (4342): calculate z from d using the lens-maker's formula
Step C (4344): Use algorithms 41A, 42A or 42B to find nearest object.
Step D (4346): If no object is found, algorithm stops.
Step E (4348): If object is found, the GET_SHARP operation is performed to extract image of only the object OC from O
Step F (4350): I1 and I2 are calculated by FIM operations on OC upon front image sensor 4313 and back image sensor 4314 respectively: I1=FIM(OC, d, z1), I2=FIM(OC, d, z2)
Step G (4352): The sensor image data S1 and S2 are updated by subtracting I1 and I2 respectively.
Step H (4354): d is incremented to look for the next object.
Algorithm 42A or Algorithm 42B may then be applied to differential scene 4530 to reconstruct the image. If multiple dynamic objects are present in the scene, Algorithm 43A may be used to track and reconstruct the objects.
Step A (4540): Start at t=t0
Step B (4542): Store sensor data S1 and S2 at t=t0
Step C (4544): Increment time by time-step ts: t:=t+ts
Step D (4546): Store sensor data S1 and S2 at new time t
Step E (4548): Calculate differential sensor data by subtracting sensor data S1 and S2 of previous time-step from sensor data S1 and S2 of current time-step, eliminating images of static objects.
Step F (4550): Perform Algorithm 43A with differential sensor data as inputs S1 and S2
Step G: Go back to Step C (4544) and continue until desired.
Pixel alignment of the perpendicular image sensor 4613 and parallel image sensor 4614 may be achieved using the method described by
The image sensor 4653 may be actuated between two positions of distances z1 and z2 from the lens 4652. z1 is the location of image focal plane 4659 which corresponds to another plane 4656 at distance d1 from the lens 4652 on its real side, while z2 is the location of image focal plane 4658 which corresponds to another plane 4657 at distance d2 from the lens 4652 on its real side. The real workspace on the real side of the lens 4652 is bounded by plane 4656 and plane 4657 at distances d1 and d2 respectively from the lens 4652. The image sensor 4653 stores images of scenes within the real workspace when it is at locations z1 and z2 from the lens 4652. In this manner, it is behaving like two independent image sensors located at distances z1 and z2 from the lens 4652, similar to the imaging system 4110, and may have the advantage of not attenuating any of the light coming from the scene. The actuation motor 4654 may be a type of piezoelectric drive which typically has maximum linear speeds of 800,000 microns per second and precision of a few nanometers. For example, with a real workspace defined by the space from 1 to 10 meters from the lens of typical focal length about 5 mm, the distance between z1 and z2 with air in between will be about 22.5 microns, which allows the image sensor 4653 to move back and forth between the positions z1 and z2 at a rate of more than 15,000 times per second. Typically, this will be enough for a camera system to collect the two images where the frame rate is about 30 frames per second, even accounting for shutter speed and shutter delay. The collected images from image sensor array 4653 may be processed and stored by an integrated image processor and memory system 4151 connected to the image sensor array 4653.
Pixel alignment of the image sensor 4653 along the rails 4660 specifically at positions z1 and z2 may be achieved using the method described by
Several material systems have been illustrated as examples for various embodiments of this invention in this patent application. It will be clear to one skilled in the art based on the present disclosure that various other material systems and configurations can also be used without violating the concepts described. It will also be appreciated by persons of ordinary skill in the art that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the invention includes both combinations and sub-combinations of the various features described herein above as well as modifications and variations which would occur to such skilled persons upon reading the foregoing description. Thus the invention is to be limited only by the appended claims.
Or-Bach, Zvi, Sekar, Deepak C., Cronquist, Brian
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